library(tidyverse)
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library(ggplot2)
library(plotly)
## Warning: package 'plotly' was built under R version 4.2.2
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## Attaching package: 'plotly'
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## The following object is masked from 'package:ggplot2':
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## last_plot
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## filter
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## The following object is masked from 'package:graphics':
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## layout
energy = read_csv("archive/organised_Gen.csv")
## New names:
## Rows: 496774 Columns: 7
## ── Column specification
## ──────────────────────────────────────────────────────── Delimiter: "," chr
## (3): STATE, TYPE OF PRODUCER, ENERGY SOURCE dbl (4): ...1, YEAR, MONTH,
## GENERATION (Megawatthours)
## ℹ Use `spec()` to retrieve the full column specification for this data. ℹ
## Specify the column types or set `show_col_types = FALSE` to quiet this message.
## • `` -> `...1`
colnames(energy) = c("ID", "year", "month", "state", "producer", "source", "generation")
energy = energy %>% select(-`ID`)
energy %>%
filter(producer == "Total Electric Power Industry", state == "US-TOTAL") %>%
ggplot() +
geom_point(aes(x = year, y = generation, color = source)) +
geom_smooth(aes(x = year, y = generation, color = source)) +
labs(title = "US total power generation per year")
## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
energy %>%
filter(producer == "Total Electric Power Industry", state == "TX") %>%
ggplot() +
geom_point(aes(x = year, y = generation, color = source)) +
geom_smooth(aes(x = year, y = generation, color = source)) +
labs(title = "Texas total power generation per year")
## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
energy %>%
filter(producer == "Total Electric Power Industry", state != "US-TOTAL") %>%
ggplot() +
geom_point(aes(x = state, y = generation, color = source))
energy %>%
filter(producer == "Total Electric Power Industry", state != "US-TOTAL", generation < -5000) %>%
ggplot() +
geom_point(aes(x = state, y = generation, color = source)) +
labs(title = "States with negative power generation (<-5000)")
energy %>%
filter(producer == "Total Electric Power Industry", state == "TX") %>%
ggplot() +
geom_point(aes(x = month, y = generation, color = source)) +
geom_smooth(aes(x = month, y = generation, color = source)) +
labs(title = "Texas total power generation per month")
## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
energy %>%
ggplot() +
geom_col(aes(x = year, y = generation, fill = source)) +
facet_wrap(vars(source))
US goal is to install an average of 30 GW of solar capacity per year between now and 2025 and 60 GW per year from 2025-2030. https://www.renewable-ei.org/pdfdownload/activities/01_Key_AlejandroMoreno.pdf
total_energy = energy %>% filter(producer == "Total Electric Power Industry", state != "US-TOTAL")
fig = energy %>%
filter(producer == "Total Electric Power Industry", state != "US-TOTAL") %>%
group_by(year, month, state) %>%
summarize(total = sum(generation)/2) %>%
right_join(total_energy) %>%
filter(source != "Total") %>%
ggplot() +
geom_col(aes(x = state, y = generation, fill = source))
## `summarise()` has grouped output by 'year', 'month'. You can override using the
## `.groups` argument.
## Joining, by = c("year", "month", "state")
ggplotly(fig, tooltip = "y")
energy %>% filter(producer == "Total Electric Power Industry", state != "US-TOTAL", source != "Total") %>%
group_by(year, month)
## # A tibble: 117,747 × 6
## # Groups: year, month [257]
## year month state producer source gener…¹
## <dbl> <dbl> <chr> <chr> <chr> <dbl>
## 1 2001 1 AK Total Electric Power Industry Coal 46903
## 2 2001 1 AK Total Electric Power Industry Petroleum 71085
## 3 2001 1 AK Total Electric Power Industry Natural Gas 367521
## 4 2001 1 AK Total Electric Power Industry Hydroelectric Conven… 104549
## 5 2001 1 AK Total Electric Power Industry Wind 87
## 6 2001 1 AL Total Electric Power Industry Coal 6557913
## 7 2001 1 AL Total Electric Power Industry Petroleum 107497
## 8 2001 1 AL Total Electric Power Industry Natural Gas 566478
## 9 2001 1 AL Total Electric Power Industry Other Gases 25283
## 10 2001 1 AL Total Electric Power Industry Nuclear 2940300
## # … with 117,737 more rows, and abbreviated variable name ¹generation